Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/15341
Título: Desempenho de Intervalos de confiança para a média de populações Poisson avaliado por simulação Monte Carlo
Título(s) alternativo(s): Performance of confidence intervals for the mean of Poisson populations evaluated by Monte Carlo simulations
Palavras-chave: Aproximação normal da Poisson
Comprimento de intervalo
Probabilidade de cobertura
Simulação de Monte Carlo
Normal approximation of Poisson
Interval length
Coverage probability
Monte Carlo Simulation
Data do documento: Jul-2013
Editor: Universidade Estadual Paulista
Citação: CORRÊA, C. B. V.; FERREIRA, D. F. Desempenho de Intervalos de confiança para a média de populações Poisson avaliado por simulação Monte Carlo. Revista Brasileira de Biometria, São Paulo, v. 31, n. 3, p. 423-440, jul./set. 2013.
Resumo: Many approximations to confidence intervals for the parameter λ of a Poisson population exist in the literature. The present work was made with the main objective to evaluate, by simulation, the proprieties of asymptotes procedures to confidence interval for the parameter λ of Poisson. Three asymptotic and the exact intervals were studied. The simulations were performed in R statistical software. The specific objectives were reach an explicit solution for Hall (1982)'s interval and generalize the Begaud (2005)'s interval for the case where n>1. As proposed, an explicit solution for the interval of Hall (1982) has been achieved. The approximated confidence interval of Begaud (2005) was generalized to sample sizes greater than 1. The three asymptotic intervals have shown equivalent performance to the exact interval with respect to the coverage probability to λ≥5 and n>1. With n=1 and λ≥5, the Begaud (2005) interval show the best performance. Regards to the interval lengths, for λ≥5 and n>1, the performance of the confidence intervals followed the order, from the best (shorter) to the worst (longest) case: Hall (1982), Ferreira (2009), Begaud 2005) and exact. As in small samples, for small values of λ, the approximations had low performance and λ is unknown, it is recommended to use the exact interval, except when some results should be built and exact theories are not available and are difficult or impossible to construct.
URI: http://jaguar.fcav.unesp.br/RME/fasciculos/v31/v31_n3/A7_Cassio_Daniel.pdf
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